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About the Role
The World Bank Group (WBG) is seeking a Data Scientist to lead the design and implementation of advanced data analytics frameworks, support the development of data-driven innovation strategies, and build internal capacity for evidence-based decision-making. This role is crucial in advancing the WBG's transformation and accelerating impact through data-driven solutions.
Responsibilities
- Operationalize and continuously improve the Innovation Analytics methodology using AI and ML for innovation identification, classification, and analysis across WBG portfolios.
- Combine ontology-based concepts, semantic embeddings, LLM-assisted analysis, NLP, and other statistical and machine-learning methods on structured and unstructured data.
- Build reproducible data and analytical pipelines for document ingestion, text extraction, innovation detection, lifecycle and maturity classification, replication and diffusion analysis, and portfolio-level aggregation.
- Design and implement rigorous validation and quality-assurance approaches, including expert validation, sampling, error analysis, confidence assessment, and monitoring of false positives and negatives.
- Apply the methodology to various WBG use cases, translating management questions into appropriate datasets, analytical approaches, and decision-relevant outputs.
- Develop clear analytical products and visualizations to identify portfolio patterns, replication and scaling opportunities, capability gaps, and strategic insights.
- Document analytical methods, data transformations, assumptions, validation results, limitations, and methodology changes.
- Contribute to standardizing and scaling the Innovation Analytics service.
Requirements
- Master’s degree in data science, computer science, statistics, economics, applied mathematics, or a related quantitative field.
- Minimum of five years of relevant professional experience.
- Strong applied experience in machine learning and natural language processing (NLP), including text classification, semantic embeddings and search, information extraction, or related analysis of large unstructured text collections.
- Demonstrated experience using large language models (LLMs) programmatically for classification, extraction, structured analysis, or similar analytical tasks, including prompt design, systematic validation, and understanding of generative AI limitations.
- Advanced proficiency in Python and SQL.
- Strong skills in data management, statistical analysis, data visualization, version control, and reproducible analytical workflows.
- Strong grounding in quantitative research methods and model evaluation, including sampling and validation, precision/recall trade-offs, error analysis, confidence assessment, and rigorous interpretation of analytical results.
- Demonstrated ability to translate complex management and operational questions into tractable analytical approaches.
- Demonstrated ability to synthesize and visualize findings across sectors, countries, datasets, and analytical methods for technical and non-technical audiences.
- Strong initiative, results orientation, and teamwork skills.
- Ability to work effectively across multidisciplinary teams and evolving priorities.
- Ability to collaborate effectively across teams, disciplines, cultures, and institutional boundaries.
- Ability to responsibly leverage digital and AI-enabled tools to enhance productivity, learning, and decision-making.
- Experience working in fragile, conflict-affected, and violent (FCV) contexts is encouraged.
Skills
- Machine learning
- Natural language processing (NLP)
- Text classification
- Semantic embeddings
- Search
- Information extraction
- Analysis of large unstructured text collections
- Large language models (LLMs)
- Prompt design
- Systematic validation
- Python
- SQL
- Data management
- Statistical analysis
- Data visualization
- Version control
- Reproducible analytical workflows
- Quantitative research methods
- Model evaluation
- Sampling
- Validation
- Precision/recall trade-offs
- Error analysis
- Confidence assessment
- Ontologies
- Interactive data visualization tools and libraries
- User-facing system design
- Analytical product design
- Interoperability with APIs and data schemas
- Development finance
- MDB operational data
- Vector databases/RAG
- Retrieval systems
- LLM agent engineering
Location
- Washington, DC, United States
Work Type
- International Recruitment
- Open-Ended Staff
Experience Level
- Minimum of five years of relevant professional experience
Education Level
- Master’s degree in data science, computer science, statistics, economics, applied mathematics, or a related quantitative field
Benefits
- Retirement plan
- Medical insurance
- Life insurance
- Disability insurance
- Paid leave
- Parental leave
- Reasonable accommodations for individuals with disabilities
About the Company
- At the World Bank Group (WBG), you’ll join a diverse, global community working across cultures, disciplines, and borders to address the world’s most pressing development challenges.
- The WBG is in the midst of a significant institutional transformation, unifying knowledge and financial systems to accelerate impact, boost efficiency, and deliver greater value to clients.
- The Partnerships, Innovation, and Mobilization Vice Presidency (PIM) is a newly established World Bank Group Vice Presidency that brings together the institution’s work on IDA policy and resource mobilization, partnerships, trust funds, financial intermediary funds (FIFs), co-financing, and innovation.
- The Department for Innovation develops and pilots new initiatives and drives forward-thinking approaches to address complex development challenges facing the world today.
Equal Opportunity
- We are proud to be an equal opportunity and inclusive employer with a dedicated and committed workforce, and do not discriminate based on gender, gender identity, religion, race, ethnicity, sexual orientation, or disability.